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Real-time semi-partitioned scheduling of fork-join tasks using work-stealing

dc.contributor.authorMaia, Cláudio
dc.contributor.authorMeumeu Yomsi, Patrick
dc.contributor.authorNogueira, Luís Miguel
dc.contributor.authorPinho, Luís Miguel
dc.date.accessioned2018-01-11T14:40:35Z
dc.date.available2018-01-11T14:40:35Z
dc.date.issued2017
dc.description.abstractThis paper extends the work presented in Maia et al. (Semi-partitioned scheduling of fork-join tasks using work-stealing, 2015) where we address the semi-partitioned scheduling of real-time fork-join tasks on multicore platforms. The proposed approach consists of two phases: an offline phase where we adopt a multi-frame task model to perform the task-to-core mapping so as to improve the schedulability and the performance of the system and an online phase where we use the work-stealing algorithm to exploit tasks’ parallelism among cores with the aim of improving the system responsiveness. The objective of this work is twofold: (1) to provide an alternative scheduling technique that takes advantage of the semi-partitioned properties to accommodate fork-join tasks that cannot be scheduled in any pure partitioned environment and (2) to reduce the migration overheads which has been shown to be a traditional major source of non-determinism for global scheduling approaches. In this paper, we consider different allocation heuristics and we evaluate the behavior of two of them when they are integrated within our approach. The simulation results show an improvement up to 15% of the proposed heuristic over the state-of-the-art in terms of the average response time per task set.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1186/s13639-017-0079-5pt_PT
dc.identifier.issn1687-3963
dc.identifier.urihttp://hdl.handle.net/10400.22/10758
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerOpenpt_PT
dc.relation.publisherversionhttps://jes-eurasipjournals.springeropen.com/articles/10.1186/s13639-017-0079-5pt_PT
dc.subjectParallel taskspt_PT
dc.subjectSemi-partitioned schedulingpt_PT
dc.subjectWork-stealingpt_PT
dc.subjectMulticore platformspt_PT
dc.titleReal-time semi-partitioned scheduling of fork-join tasks using work-stealingpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage14pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleEURASIP Journal on Embedded Systemspt_PT
person.familyNamePinho
person.givenNameLuis Miguel
person.identifier.ciencia-id8112-2108-F3B2
person.identifier.orcid0000-0001-6888-1340
person.identifier.ridM-3416-2013
person.identifier.scopus-author-id6602594556
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationfd791145-af93-47d9-bbe8-647a326d2f39
relation.isAuthorOfPublication.latestForDiscoveryfd791145-af93-47d9-bbe8-647a326d2f39

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